Current development—Over the last years, the rapid development in digital technology has considerably changed the character and the importance of wireless communications in modern society. The data-based applications are becoming more and more important compared to speech transmission, which up to the middle 90ies was the only relevant application in the second-generation mobile radio standard (GSM; GSM=global standard for mobile communications). The change began inconspicuously with making short message services (SMS) popular and subsequently extending the GSM network with higher-rate services (GPRS; GPRS=general packet radio service). In the meantime, the high-rate and partially real-time capable data services have become a fixed mainstay in the third-generation mobile radio standard (UMTS; UMTS=universal mobile telephone system) and will even more rise in importance in the upcoming cellular standards (Beyond 3G).
Nowadays, the most popular data-based user activities in the UMTS network include exchanging multimedia messages (MMS; MMS=multimedia message service), using different download services (music, ring tones) and partly even video telephony, for example. However, the expansion of wireless data services is not limited to cellular mobile radio. It contributed to making the so-called ad hoc network concept popular in private households, which represents a self-organized kind of communication with multiple users and multiple services and, as a rule, does without superordinated communication nodes (as the basis station in the cellular concept) and, thus, is based on physical direct connections between data sources and data sinks. The ad hoc mode is the main principle of operation in the wireless communication standards of the IEEE. The wireless ad hoc applications are numerous both in the industrial and in the private sector and have excellent prospects for the future. The most illustrative examples of use include exchanging large amounts of data between two terminals in different office rooms, a real-time capable instant, i.e. immediate, speech and/or image connection between two remote rooms of a detached house/office building or a wireless sensoric monitoring of an important area (sensor network), for example.
Quality of service in wireless networks—The quality of service (QoS) is experienced by end users subjectively according to criterions such as speech intelligibility, speed of data transfer, and steadiness of the real-time data connection (not jerky). From the engineering point of view, the perceptive criterions as the entirety of all perceptions are associated with so-called QoS parameters. In this context, the level of the signal to interference ratio (SIR, SINR=signal to interference and noise ratio), for example, which is expressed in decibel, may mirror e.g. the speech intelligibility, the data rate (in [bit/s]) corresponds to the transfer speed and the delay times (in [s]) of the data packets are directly related to the real-time capability. Logically, due to the limitation of network resources such as transmission power and bandwidth, it cannot be ruled out that with multiple connections being active at the same time, some end users experience a deficitary quality of service. In this context, the crosstalk between the connections (interference) represents a crucial additional destructive factor. Crosstalk may be avoided by alternately assigning separate time slots, or separating the frequency bands of all connections. However, particularly in ad hoc networks this possibility is out of question due to the high control and synchronization effort.
An example of an ad hoc network with a degradation in the quality of service by interference: four notebooks are located in one office room. The notebooks have pairwise simultaneously set up high-rate wireless direct ad hoc connections, e.g. for transferring two large amounts of data. Due to the relatively small distance between the adjacent transmitters and receivers of both connections, the transmit signals strongly interfere with the receive signals at the respective receivers. This has a destructive influence on the data rates and, thus, on the duration of the both connections. Thus, the both connections need (much) more time for completing the transfer than it would be the case in a single operation.
Optimum allocation of resources—In realistic cases of application, it is not possible to improve the quality of service by increasing the power and bandwidth budgets, due to legal limitations on the transmit signal level on the one hand, and due to the limitation of useable frequency bands (the first and second ISM band, the licensed UMTS bands) on the other hand. For these reason, optimizing the allocation of resources between the network nodes plays an extremely important role. Under consideration of the character of the different connections, it allows the optimum translation of the present power and bandwidth budget into the quality of service perceived by the end users.
Realization of the optimum allocation of resources—The key to efficient allocation of resources lies in the performance of the optimization procedures used, which in the invention are exclusively iterative in nature. What is meant by optimization procedure is the connection of the iterative optimization algorithm with the schemes of the signaling and the feedback signaling between nodes in the network necessary for performing the iterations. What is meant by signaling is the transmission of all data necessitated for controlling the network. The signaling data are thus to be distinguished from the information data containing the actual information to be transmitted.
Online optimization problems—The fast-moving nature of today's networks represents one of the crucial challenges to the algorithms and their implementation. Due to the mobility of the network nodes and packet-oriented data transmission, for example, modern data networks comprise a fast time variability of the topology and data traffic structure. Here, the optimum re-allocation of the resources may follow the time pattern of the changes in topology and data traffic only with a tolerable delay (online optimization). Consequently, apart from accuracy, the implemented algorithms have to comprise sufficiently good convergent properties, that is, they have to achieve the final result fast. As has been shown in practice, these difficulties in cellular communication may easily be overcome. Thanks to a more or less unrestricted energy consumption and a large computing capacity, the basis station allows the implementation of highly complex optimization algorithms. Therefore, it is capable of following the network changes and for timely arranging the re-allocation of the resources in the network, if necessary. In this context, due to the common battery operation of the network nodes and the limitation of device costs per node, the ad hoc networks reach limits determined by energy and computational performance. This contributes to increased requirements with respect to complexity and convergence speed of the optimization procedures used.
Problems in local network knowledge—In cellular networks, the basis station typically has a global knowledge of the network in the form of channel states (the prerequisite for this is the so-called reciprocity of the channel, which, however, is valid in all network scenarios relevant for the practice), kinds of data traffic and requirements with respect to the quality of service, and, thus, is predestinated for the centralized execution of the online optimization of the allocation of resources. By signaling, it arranges for the (re)allocation of the resources only after each optimization pass—for the uplink—or it (re)allocates its resources itself—for the downlink. A similar procedure in ad hoc networks is inhibited by their decentralization, which means that, as a rule, none of the network nodes is superordinated and, thus, the global knowledge of the network parameters, i.e. the channel states between all nodes (transmit nodes, receive nodes) or the strengths of the interference between all connections, is not present at any of the nodes. As a rule, network nodes have at most local knowledge of the network, e.g. in the form of channel states or interference strengths in the close environment, which may originate from a local signaling between the neighbor nodes. One of the important reasons for the absence of the global network knowledge at the nodes in the ad hoc network may be the spatial distribution of the network. In such a case, the receive nodes might not be directly accessible by the transmit nodes under some circumstances, and, thus, the latter are forced to communicate via intermediate nodes (so-called “multi-hop transmission”). However, the value of the invention becomes already apparent when considering the cellular and so-called one-hop ad hoc networks, i.e. such which allow direct connections over the full area. Therefore, an explicit consideration of multi-hop problems is omitted in this document, to which, however, the invention may be analogously applied.
Concept of the centralized realization of allocation of online resources—A possibility to overcome this difficulty in ad hoc networks is to introduce a virtual cellular infrastructure by nominating a superordinated node to which the global knowledge of the network parameters is provided by transmission of the local knowledge of all nodes. The nominated node takes on the function of the basis station, performs a centralized optimization and arranges for a (re)allocation of the resources in the network by signaling. In ad hoc networks, the realization of the allocation of online resources by help of the virtual cellular structure is the most obvious concept. Here, the advantage lies in the applicability of centralized optimization algorithms based on a well-developed general algorithmic optimization theory. Over the last years, numerous network-specific algorithmic solutions for special criterions for the allocation of resources have developed. The significant disadvantage of the realization approach with a virtual cellular structure lies in the signaling necessitating a lot of effort which, on the one hand, significantly delays the (re)allocation of the resources and, on the other hand, is a burden to the battery runtimes of all network nodes. It is the virtual basis station (the nominated nodes) in particular which has to perform calculation operations necessitating a lot of effort that is at a disadvantage.
Concept of the decentralized realization of the allocation of online resources—Taking the afore-mentioned considerations into account, the competing realization concept based on distributed network actions without global cooperation is the more advantageous one for ad hoc networks. In this concept, the network nodes follow a fixed local action scheme, which, as a rule, is iterative in nature, independently of each other. Local signaling may also belong to the individual steps of the scheme, e.g. with respect to the neighbor nodes or to a specific node. The more effort the signaling necessitates, the smaller its advantage over the concept of the centralized realization. The result of such actions distributed in the network is the knowledge of optimum assignments of resources at the respective network nodes. In the last years, some decentralized optimization procedures for diverse criterions for the allocation of resources have been developed. However, for the majority of the relevant allocation criterions, decentralized realization concepts worth mentioning do not yet exist.
As already set forth above, the main problem in the implementation of iterative algorithms for determining the optimum allocation of transmission power in distributed wireless mobile radio networks without any central control unit is to obtain global information necessitated for performing the iteration loops, which is distributed as a gradient of the transmission power in the network.
Known common solution approaches: Usually, global information is exchanged between all nodes by help of a “flooding protocol”. This is the simplest algorithm for information distribution in a distributed network. In this process, an initiator locally sends a message to all its neighbors. Each which obtains the message and has not been informed yet passes it on to all its neighbors, compare publication by Mung Chiang, “Balancing Transport and Physical Layers in Wireless Multihop Networks: Jointly Optimal Congestion Control ans Power Control” (IEEE Journal of Selected Areas in Communications, Vol. 23, No. 1, January 2005, pp. 104-116), on which the present invention is based. However, such a procedure leads to wasting scarce resources (bandwidth and power) in mobile radio systems and, thus, is inacceptable for many applications.